[Skip to Content]
[Skip to Content Landing]
Table 1.  
Demographic and Health Comorbidity Characteristics of the NHANES and NHATS Study Populations
Demographic and Health Comorbidity Characteristics of the NHANES and NHATS Study Populations
Table 2.  
Unweighted Frequencies of Vision Assessment From NHANES and NHATS
Unweighted Frequencies of Vision Assessment From NHANES and NHATS
Table 3.  
Linear and Logistic Regression Models of VI for DSST Performance Using NHANES (1999-2002)
Linear and Logistic Regression Models of VI for DSST Performance Using NHANES (1999-2002)
Table 4.  
Logistic Regression Models of Self-reported Visual Impairment for Dementia Status in NHATS (2011-2015)
Logistic Regression Models of Self-reported Visual Impairment for Dementia Status in NHATS (2011-2015)
1.
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States.  Arch Ophthalmol. 2004;122(4):477-485.PubMedGoogle ScholarCrossref
2.
Evans  JR, Fletcher  AE, Wormald  RP,  et al.  Prevalence of visual impairment in people aged 75 years and older in Britain: results from the MRC trial of assessment and management of older people in the community.  Br J Ophthalmol. 2002;86(7):795-800.PubMedGoogle ScholarCrossref
3.
Tielsch  JM, Sommer  A, Witt  K, Katz  J, Royall  RM.  Blindness and visual impairment in an American urban population: the Baltimore Eye Survey.  Arch Ophthalmol. 1990;108(2):286-290.PubMedGoogle ScholarCrossref
4.
Graham  JE, Rockwood  K, Beattie  BL,  et al.  Prevalence and severity of cognitive impairment with and without dementia in an elderly population.  Lancet. 1997;349(9068):1793-1796.PubMedGoogle ScholarCrossref
5.
Hedden  T, Gabrieli  JDE.  Insights into the ageing mind: a view from cognitive neuroscience.  Nat Rev Neurosci. 2004;5(2):87-96.PubMedGoogle ScholarCrossref
6.
Brookmeyer  R, Johnson  E, Ziegler-Graham  K, Arrighi  HM.  Forecasting the global burden of Alzheimer’s disease.  Alzheimers Dement. 2007;3(3):186-191.PubMedGoogle ScholarCrossref
7.
Prince  M, Wimo  A, Guerchet  M,  et al. World Alzheimer Report 2015: the Global Impact of Dementia analysis of prevalence, incidence, cost, and trends. http://www.alz.co.uk.laneproxy.stanford.edu/research/WorldAlzheimerReport2015.pdf. Accessed August 19, 2016.
8.
Varma  R, Vajaranant  TS, Burkemper  B,  et al.  Visual impairment and blindness in adults in the united states: demographic and geographic variations from 2015 to 2050.  JAMA Ophthalmol. 2016;134(7):802-809.PubMedGoogle ScholarCrossref
9.
Ong  SY, Cheung  CY, Li  X,  et al.  Visual impairment, age-related eye diseases, and cognitive function: the Singapore Malay Eye study.  Arch Ophthalmol. 2012;130(7):895-900.PubMedGoogle ScholarCrossref
10.
Clemons  TE, Rankin  MW, McBee  WL; Age-Related Eye Disease Study Research Group.  Cognitive impairment in the Age-Related Eye Disease Study: AREDS report no. 16.  Arch Ophthalmol. 2006;124(4):537-543.PubMedGoogle ScholarCrossref
11.
Baker  ML, Wang  JJ, Rogers  S,  et al.  Early age-related macular degeneration, cognitive function, and dementia: the Cardiovascular Health Study.  Arch Ophthalmol. 2009;127(5):667-673.PubMedGoogle ScholarCrossref
12.
Bowen  M, Edgar  DF, Hancock  B,  et al. The Prevalence of Visual Impairment in People with Dementia (the PrOVIDe study): a cross-sectional study of people aged 60-89 years with dementia and qualitative exploration of individual, carer and professional perspectives. In:  Health Services and Delivery Research. Southampton, England: NIHR Journals Library; 2016.
13.
Pham  TQ, Kifley  A, Mitchell  P, Wang  JJ.  Relation of age-related macular degeneration and cognitive impairment in an older population.  Gerontology. 2006;52(6):353-358.PubMedGoogle ScholarCrossref
14.
Woo  SJ, Park  KH, Ahn  J,  et al.  Cognitive impairment in age-related macular degeneration and geographic atrophy.  Ophthalmology. 2012;119(10):2094-2101.PubMedGoogle ScholarCrossref
15.
Rait  G, Fletcher  A, Smeeth  L,  et al.  Prevalence of cognitive impairment: results from the MRC trial of assessment and management of older people in the community.  Age Ageing. 2005;34(3):242-248.PubMedGoogle ScholarCrossref
16.
Garin  N, Olaya  B, Lara  E,  et al.  Visual impairment and multimorbidity in a representative sample of the Spanish population.  BMC Public Health. 2014;14:815-825.PubMedGoogle ScholarCrossref
17.
Court  H, McLean  G, Guthrie  B, Mercer  SW, Smith  DJ.  Visual impairment is associated with physical and mental comorbidities in older adults: a cross-sectional study.  BMC Med. 2014;12:181-188.PubMedGoogle ScholarCrossref
18.
Mangione  CM, Seddon  JM, Cook  EF,  et al.  Correlates of cognitive function scores in elderly outpatients.  J Am Geriatr Soc. 1993;41(5):491-497.PubMedGoogle ScholarCrossref
19.
Salthouse  TA, Hancock  HE, Meinz  EJ, Hambrick  DZ.  Interrelations of age, visual acuity, and cognitive functioning.  J Gerontol B Psychol Sci Soc Sci. 1996;51(6):317-330.PubMedGoogle ScholarCrossref
20.
Lin  FR, Metter  EJ, O’Brien  RJ, Resnick  SM, Zonderman  AB, Ferrucci  L.  Hearing loss and incident dementia.  Arch Neurol. 2011;68(2):214-220.PubMedGoogle ScholarCrossref
21.
Lin  FR.  Hearing loss and cognition among older adults in the United States.  J Gerontol A Biol Sci Med Sci. 2011;66(10):1131-1136.PubMedGoogle ScholarCrossref
22.
Lin  FR, Yaffe  K, Xia  J,  et al; Health ABC Study Group.  Hearing loss and cognitive decline in older adults.  JAMA Intern Med. 2013;173(4):293-299.PubMedGoogle ScholarCrossref
23.
Gurgel  RK, Ward  PD, Schwartz  S, Norton  MC, Foster  NL, Tschanz  JT.  Relationship of hearing loss and dementia: a prospective, population-based study.  Otol Neurotol. 2014;35(5):775-781.PubMedGoogle ScholarCrossref
24.
Dupuis  K, Pichora-Fuller  MK, Chasteen  AL, Marchuk  V, Singh  G, Smith  SL.  Effects of hearing and vision impairments on the Montreal Cognitive Assessment.  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2015;22(4):413-437.PubMedGoogle ScholarCrossref
25.
Lin  MY, Gutierrez  PR, Stone  KL,  et al; Study of Osteoporotic Fractures Research Group.  Vision impairment and combined vision and hearing impairment predict cognitive and functional decline in older women.  J Am Geriatr Soc. 2004;52(12):1996-2002.PubMedGoogle ScholarCrossref
26.
Yamada  Y, Denkinger  MD, Onder  G,  et al.  Dual sensory impairment and cognitive decline: the results from the Shelter Study.  J Gerontol A Biol Sci Med Sci. 2016;71(1):117-123.PubMedGoogle ScholarCrossref
27.
Won  H, Singh  DK, Din  NC,  et al.  Relationship between physical performance and cognitive performance measures among community-dwelling older adults.  Clin Epidemiol. 2014;6:343-350.PubMedGoogle Scholar
28.
Centers for Disease Control and Prevention; National Center for Health Statistics. National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes.htm/. Published 2016. Accessed December 19, 2016.
29.
Proust-Lima  C, Amieva  H, Dartigues  J-F, Jacqmin-Gadda  H.  Sensitivity of four psychometric tests to measure cognitive changes in brain aging-population-based studies.  Am J Epidemiol. 2007;165(3):344-350.PubMedGoogle ScholarCrossref
30.
National Institute on Aging Health ABC Operations Manual. Digit symbol substitution test. https://healthabc.nia.nih.gov/sites/default/files/dsst_0.pdf. Accessed March 7, 2017.
31.
Rosano  C, Newman  AB, Katz  R, Hirsch  CH, Kuller  LH.  Association between lower digit symbol substitution test score and slower gait and greater risk of mortality and of developing incident disability in well-functioning older adults.  J Am Geriatr Soc. 2008;56(9):1618-1625.PubMedGoogle ScholarCrossref
32.
Swindell  WR, Cummings  SR, Sanders  JL,  et al.  Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.  Rejuvenation Res. 2012;15(4):405-413.PubMedGoogle ScholarCrossref
33.
Chou  R, Dana  T, Bougatsos  C, Grusing  S, Blazina  I.  Screening for impaired visual acuity in older adults: Updated evidence report and systematic review for the us preventive services task force.  JAMA. 2016;315(9):915-933.PubMedGoogle ScholarCrossref
34.
National Health and Aging Trends Study (NHATS) User Guide. https://healthabc.nia.nih.gov/sites/default/files/dsst_0.pdf. Accessed February 2, 2017.
35.
STATA programming statements for construction of dementia classification in the National Health and Aging Trends Study. https://www.nhats.org/scripts/documents/NHATS_Addendum_to_Technical_Paper_5_STATA_Programming_Statements_Jul2013.pdf. Accessed February 5, 2017.
36.
Classification of Persons by Dementia Status in the National Health and Aging Trends Study. https://www.nhats.org/scripts/documents/DementiaTechnicalPaperJuly_2_4_2013_10_23_15.pdf. Accessed February 2, 2017.
37.
Addendum to classification of persons by dementia status in the National Health and Aging Trends Study for rounds 2-5. https://www.nhats.org/scripts/documents/NHATS_Dementia_Classification_Addendum_Rounds_2_5.pdf. Accessed May 30, 2017.
38.
Teutsch S, McCoy M, Woodbury B, Welp A, et al. Making eye health a population health imperative: vision for tomorrow: a report of the national academies of sciences, engineering, and medicine health and medicine division. http://www.nationalacademies.org/hmd/Reports/2016/making-eye-health-a-population-health-imperative-vision-for-tomorrow.aspx. Published 2016. Accessed October 20, 2016.
39.
US Preventive Services Task Force.  Screening for impaired visual acuity in older adults: US Preventive Services Task Force recommendation statement.  Ann Intern Med. 2009;151(1):37-43, W10.PubMedGoogle ScholarCrossref
40.
Lee  P.  Visual acuity screening among asymptomatic older adults.  JAMA. 2016;315(9):875-876.PubMedGoogle ScholarCrossref
41.
Smeeth  L, Iliffe  S.  Community screening for visual impairment in the elderly.  Cochrane Database Syst Rev. 2006;(3):CD001054. PubMedGoogle Scholar
42.
Sommer  A.  The USPSTF position on vision screening of adults—seeing is believing?  JAMA Intern Med. 2016;176(4):438-439.PubMedGoogle ScholarCrossref
43.
Parke  DW  II, Repka  MX, Lum  F.  The US Preventive Services Task Force recommendation on vision screening in older adults: a narrow view.  JAMA Ophthalmol. 2016;134:485-486.PubMedGoogle ScholarCrossref
44.
US Department of Health and Human Services; Office of Disease Prevention and Health Promotion. Healthy People 2020 Topics and Objectives: vision. https://www.healthypeople.gov/2020/topics-objectives/topic/vision. Accessed September 19, 2016.
45.
West  SK, Lee  P.  Vision surveillance in the United States: has the time come?  Am J Ophthalmol. 2012;154:S1-S2.Google ScholarCrossref
46.
National Health and Nutrition Examination Survey 1999-2000 Data Documentation, Codebook, and Frequencies: Cognitive Functioning (CFQ): Appendix 1: NHANES Digit Symbol Substitution Exercise (CFQ): Interviewer Instructions. https://wwwn.cdc.gov/Nchs/Nhanes/1999-2000/CFQ.htm#Appendix_1:__NHANES_DIGIT_SYMBOL_SUBSTITUTION_EXERCISE_(CFQ):_Interviewer_Instructions. Accessed May 30, 2017.
Original Investigation
September 2017

Association of Vision Loss With Cognition in Older Adults

Author Affiliations
  • 1Stanford University School of Medicine, Stanford, California
  • 2Center for Health Policy/Primary Care Outcomes Research, Stanford University, Palo Alto, California
  • 3Department of Medicine, Stanford University School of Medicine, Palo Alto, California
  • 4Byers Eye Institute, Department of Ophthalmology, Stanford University School of Medicine, Palo Alto, California
  • 5Veterans Affairs Palo Alto Health Care System, Palo Alto, California
JAMA Ophthalmol. 2017;135(9):963-970. doi:10.1001/jamaophthalmol.2017.2838
Key Points

Question  What is the association between visual impairment and cognitive function among older adults?

Findings  In this cross-sectional study of 2 nationally representative samples of the US population, visual impairment measured at distance, near, and by self-report was associated with 1.9- to 2.8-fold higher odds of cognitive dysfunction or dementia after adjustment for confounders.

Meaning  This study suggests that in older US adults, visual impairment is associated with lower cognitive function, highlighting the potential importance of vision screening to identify patients with eye disease as well as possible deficits in cognitive performance.

Abstract

Importance  Visual dysfunction and poor cognition are highly prevalent among older adults; however, the relationship is not well defined.

Objective  To evaluate the association of measured and self-reported visual impairment (VI) with cognition in older US adults.

Design, Setting, and Participants  Cross-sectional analysis of 2 national data sets: the National Health and Nutrition Examination Survey (NHANES), 1999-2002, and the National Health and Aging Trends Study (NHATS), 2011-2015. The NHANES was composed of a civilian, noninstitutionalized community, and the NHATS comprised Medicare beneficiaries in the contiguous United States. Vision was measured at distance, near, and by self-report in the NHANES and by self-report alone in the NHATS. Sample weights were used to ensure result generalizability.

Main Outcomes and Measures  The NHANES measured Digit Symbol Substitution Test (DSST) score and relative DSST impairment (DSST score ≤28, lowest quartile in study cohort), and the NHATS measured probable or possible dementia, classified per NHATS protocol.

Results  The NHANES comprised 2975 respondents aged 60 years and older who completed the DSST measuring cognitive performance. Mean (SD) age was 72 (8) years, 52% of participants were women (n = 1527), and 61% were non-Hispanic white (n = 1818). The NHATS included 30 202 respondents aged 65 years and older with dementia status assessment. The largest proportion (40%; n = 12 212) were between 75 and 84 years of age. Fifty-eight percent were women (n = 17 659), and 69% were non-Hispanic white (n = 20 842). In the NHANES, distance VI (β = −5.1; 95% CI, −8.6 to −1.6; odds ratio [OR], 2.8; 95% CI, 1.1-6.7) and subjective VI (β = −5.3; 95% CI, −8.0 to −2.6; OR, 2.7; 95% CI, 1.6-4.8) were both associated with lower DSST scores and higher odds of DSST impairment after full adjustment with covariates. Near VI was associated with lower DSST scores but not higher odds of DSST impairment. The NHATS data corroborated these results, with all vision variables associated with higher odds of dementia after full adjustment (distance VI: OR, 1.9; 95% CI, 1.6-2.2; near VI: OR, 2.6; 95% CI, 2.2-3.1; either distance or near VI: OR, 2.1; 95% CI, 1.8-2.4).

Conclusions and Relevance  In a nationally representative sample of older US adults, vision dysfunction at distance and based on self-reports was associated with poor cognitive function. This was substantiated by a representative sample of US Medicare beneficiaries using self-reported visual function, reinforcing the value of identifying patients with visual compromise. Further study of longitudinal interactions between vision and cognition is warranted.

Introduction

Blindness and low vision are major public health issues in the United States, affecting 1 in 28 Americans older than 40 years.1 Poor visual function increases in prevalence with age,2,3 as does a decline in cognitive function.4,5 The number of individuals with vision problems is anticipated to double by 2050, with global estimates of dementia and Alzheimer disease predicted to quadruple by 2050 owing to the rapidly aging population and increases in chronic comorbidities.6-8 During the past decade, several cross-sectional studies in the United States and abroad have revealed associations between visual and cognitive impairments in older adults.9-15 Visual impairment (VI) in older adults has also been associated with increased risks of having a diverse array of physical and mental comorbidities.16,17

Despite this body of evidence, a few studies have failed to show a direct association between cognition and vision. Most attribute correlations to age and rely on standard measurements of visual acuity (VA), with variable methods for cognitive assessment.18,19 A Spanish study demonstrated an association between self-reported visual deficits and poor cognitive function, but to our knowledge, subjective visual function has otherwise been little studied, particularly in a US population.16

Hearing loss has previously been shown to be associated with cognitive decline and dementia as well,20-23 and studies have associated dual sensory impairments in vision and audition with poor cognition in the aging population.24-26 Finally, poor physical performance has been correlated with cognitive impairment in older adults using a battery of physical functioning and cognitive assessment tests.27 Although hearing loss and physical function limitations are both possible confounders in the association between visual and cognitive impairment, we have found nothing accounting for these factors in the assessment of vision and cognition in the literature.

Quiz Ref IDIn this study, we investigate these discrepancies using a nationally representative sample of survey data, the National Health and Nutrition Examination Survey (NHANES), previously used to demonstrate a link between hearing loss and reduced cognitive function.21 Our analysis incorporates self-reported visual function as well as objective VA measurements, adjusting for comorbid hearing and physical functioning deficits, to evaluate the effect of these measures on cognitive function. Given the wide variation in potential assessment tools, particularly those used to measure cognitive function, we also performed a similar analysis in a complementary data set, the National Health and Aging Trends Study (NHATS). The NHATS is composed of a nationally representative sample of Medicare beneficiaries and provides detailed cognitive and subjective visual function data. We hypothesized that self-reported visual deficits as well as standard VA metrics will show a correlation with cognitive decline. To our knowledge, this is the first US population–based sample of this scale specifically evaluating vision and incorporating different and complementary methods of cognitive function assessment.

Methods
The NHANES Study Sample

We performed a population-based study of older American adults surveyed in the NHANES 1999 to 2002 cycles who underwent cognitive function testing. The NHANES is a national program that collects data on the health and nutrition status of the US civilian, noninstitutionalized population.28 Participants are selected through complex multistage probability sampling, with oversampling of certain subgroups.28 Sample weights provide adjusted, unbiased data generalizable to the entire US population. Cognitive function was tested on all respondents aged 60 years and older using the Digit Symbol Substitution Test (DSST), widely regarded with high sensitivity for detecting cognitive dysfunction at good baseline levels of cognition. The DSST may be a more sensitive measure of dementia than the Mini-Mental State Examination.29,30 Because there is no gold standard regarding the threshold score for which the DSST indicates cognitive impairment, we selected the lowest quartile in the study group (≤28 points) to indicate poor cognitive performance, or DSST impairment, consistent with methods previously published in the literature.11,31,32 Visual function was assessed by examination at distance and near and subjectively by questionnaire. Respondents were tested with their usual correction, and results from the better-seeing eye were used for analysis. Visual impairment was defined as worse than 20/40 in accordance with the updated guidelines from the US Preventive Services Task Force.33 Details regarding the methods for assessment of cognition, vision, and other covariates are described in the eMethods section in the Supplement.

In the 1999 to 2002 NHANES cycles, there were a total of 21 004 respondents, 3706 of whom were aged 60 years and older and 2975 of whom completed the DSST (study group). The mean (SD) age of the study group was 72 (8) years. Women made up 52% of participants (n = 1527) and 61% of participants were non-Hispanic white (n = 1818), 14% were black (n = 412), and 23% were Mexican/Hispanic (n = 671) (Table 1). Quiz Ref IDCompared with those who completed the DSST, those who did not (n = 731; 19.72%) were older, more likely to be of minority race/ethnicities, more likely to have lower education levels and lower annual household incomes, and more likely to deny smoking history but report diabetes, myocardial infarction, and stroke. They were also less likely to report hyperlipidemia (eTable 1 in the Supplement). From the study group, 425 participants (14.29%) were missing distance VA measures, 410 (13.78%) were missing near VA measures, and 28 (0.94%) were missing data on self-reported visual function. There was only 1 participant missing self-reports of hearing function and none for physical function.

The NHATS Study Sample

Because the DSST in the NHANES required visual spatial skills, we recognized that VI and cognitive impairment (as measured by the DSST) may be correlated and could confound our results. We therefore supplemented our analysis with data from the NHATS, which uses different cognitive assessment tests that are less dependent on visual function.

We investigated a sample of Medicare beneficiaries between the years 2011 and 2015 with cognitive function data in the NHATS to see whether the results corroborated those from the NHANES. The NHATS, funded by the National Institute on Aging, sampled participants from the 2011 Medicare enrollment file and interviewed them annually, with replenishment of the sample in 2015.34 Cognitive function was evaluated and categorized as probable/possible dementia vs no dementia based on a classification scheme devised by NHATS.35-37 In brief, probable dementia was defined as being diagnosed as having dementia or Alzheimer disease by a physician, as reported by either the participant or a proxy. Additionally, cognitive tests assessing memory, orientation, and function were administered, and scores at or less than 1.5 SDs from the mean in at least 1 domain qualified as possible dementia. Distance and near visual functions were reported via questionnaire. Details regarding the methods for assessment of cognition, vision, and other covariates are described in the eMethods section in the Supplement.

To conduct a cross-sectional analysis comparable with the NHANES using longitudinal data from the NHATS, surveys from participants with multiple years of follow-up were considered distinct observations. From 2011 to 2015, there were 34 190 surveys collected, of which 30 202 (88.34%) were assigned a dementia classification (study group). Thirty-five percent of the study group participants were aged 65 to 74 years, 40% were aged 75 to 84 years (n = 12 212), and 24% were older than 85 years (n = 7266). Fifty-eight percent were women (n = 17 659), and the racial/ethnic distribution was 69% non-Hispanic white (n = 20 842), 21% black (n = 6408), and 6% Mexican/Hispanic (n = 1728). Compared with those who completed the dementia evaluation, those who did not (n = 3988; 12.49%) were older, more likely to be women, and more likely to have different racial/ethnic distributions, lower education levels, and lower incomes. Additionally, none who did not complete the dementia assessment reported histories of smoking or comorbid health conditions (eTable 1 in the Supplement). From the study group, 311 participants (1.03%) were missing data for self-reported distance VI, and 385 (1.27%) were missing data for near VI. There were 129 respondents (0.43%) missing subjective hearing loss and 49 (0.16%) missing physical function impairments.

Statistical Analysis

Analyses were based on public nonidentifiable data; thus, this study was deemed exempt by the Stanford Institutional Review Board. All analyses were performed with STATA/SE, version 13.1 (StataCorp). Descriptive statistics were used to characterize the study groups and compare subgroups with and without DSST impairment (NHANES) or with and without dementia classification (NHATS). For NHANES, the 4-year examination sample weight provided for 1999 to 2002, rather than the interview sample weight, was used given that vision examination variables included in the analysis came from the subset of respondents who participated in the examination portion of the survey. For NHATS, we applied examination weights provided for each year of study data. Variance estimates were derived using Taylor Series Linearization per National Center for Health Statistics recommendations. Given the study designs of NHANES and NHATS, we used the svy set of commands in STATA.

Linear and logistic regression models (univariate and multivariate) were used to investigate the association between DSST scores and VI for NHANES. In NHATS, we modeled dementia status and subjective VI with logistic regression. Visual function was assessed independently in each regression model as distance, near, and subjective VI. All models were first adjusted for demographics and socioeconomic status (age, sex, race/ethnicity, education level, and annual household income) followed by the addition of general health conditions and behaviors (smoking status, diabetes, hypertension, hyperlipidemia or coronary heart disease, myocardial infarction, and stroke) (eTable 2 in the Supplement). Finally, fully adjusted models accounted for these variables as well as the additional effects of self-reported hearing impairment and physical limitations. Age was treated as a continuous variable in NHANES and as an interval variable (10-year increments) in NHATS based on available data. “Don’t know” and “Refuse” responses were treated as missing values and excluded from the regressions. Two-sided P values less than .05 were considered statistically significant.

Results
Demographics and Baseline Characteristics

Baseline demographics for the study samples are presented in Table 1, along with missing data for covariates. For NHANES, the unadjusted mean (SD) DSST score was 40.8 (18.7) points, with 25.85% (n = 769) scoring 28 points or lower and categorized as having DSST impairment. Compared with no DSST impairment, respondents with DSST impairment were significantly more likely to be older, of minority race/ethnicity, have less education, and have lower income. There was also a significantly higher prevalence of diabetes, myocardial infarction, and stroke among this group, while prevalence of hyperlipidemia was significantly lower. Additionally, the DSST impairment group was more likely to be male and have hypertension (not significant). For the NHATS, 24.99% (n = 7546) were classified as having dementia based on the probable or possible dementia designations. Compared with no dementia, those with dementia were significantly more likely to be older, female, of minority race/ethnicity, and have less education and lower income. They were also significantly more likely to report no smoking history but positive histories for diabetes, hypertension, coronary heart disease, myocardial infarction, and stroke.

Table 2 shows unweighted frequencies characterizing the visual function of the NHANES and NHATS study populations. For NHANES, the largest proportion of patients had good vision; however, measured distance VI was present in 9.14% of this group (n = 272), while near VI was present in 14.52% (n = 432). From self-reports, 30.08% (n = 895) felt that the general condition of their eyesight was fair to very poor and/or that their vision limited how long they could do daily activities a lot of the time to all of the time. Most participants with measured distance VA 20/40 or worse reported subjective VI; however, because patients with good measured VA (20/30 or better) outnumbered those with worse vision by 5:1, most participants with self-reported VI still had good measured VA.

In the NHATS, 7.26% of the study sample (n = 2193) reported inability to see someone across the street and/or watch television across the room, indicating distance VI, while 5.64% (n = 1704) reported inability to read newspaper print, indicating near VI (Table 2). When items querying distance and near visual function were combined to assess self-reported VI in either, the percentage of impairment increased to 10.32% (n = 3118).

Visual Function and Cognition

Table 3 and Table 4 illustrate the linear and logistic regression models evaluating the association between cognitive function and vision, both objectively measured and subjectively reported. Quiz Ref IDVisual impairment using all metrics was associated with worse DSST scores in the linear regression models, and although the associations diminished with subsequent adjustment for covariates, the results remained statistically significant (distance VI: β = −5.1; 95% CI, −8.6 to −1.6; P = .006; near VI: β = −3.8; 95% CI, −6.2 to −1.3; P = .004; subjective VI: β = −5.3; 95% CI, −8.0 to −2.6; P < .001). All measures of VI were also associated with higher odds of DSST impairment, persisting after full adjustment for distance VI (odds ratio [OR], 2.8; 95% CI, 1.1-6.7; P = .03) and subjective VI (OR, 2.7; 95% CI, 1.6-4.8; P = .001). Near VI was associated with 3.1-fold higher odds of DSST impairment (95% CI, 1.9-5.0; P < .001) when adjusted for demographics and socioeconomic status variables and 1.7-fold higher odds (95% CI, 0.9-3.4; P = .10) when further adjusted for all covariates (not significant). The NHATS results, using a dementia classification scheme to model cognitive impairment and subjective reports of distance, near, and either VI, supported the NHANES observations. All were associated with higher odds of dementia, and these associations persisted after full adjustments with covariates (distance VI: OR, 1.9; 95% CI, 1.6-2.2; P < .001; near VI: OR, 2.6; 95% CI, 2.2-3.1; P < .001; and either VI: OR, 2.1; 95% CI, 1.8-2.4; P < .001).

Discussion

Our study of a nationally representative sample of older Americans demonstrates an association between VI and worse cognitive performance as measured by the DSST (NHANES) and by assessment of dementia status (NHATS). These findings corroborate and expand on prior reports evaluating low vision or ophthalmic diseases and poor cognitive function.9-17 While many of these studies focused on specific diagnoses (eg, cataracts, age-related macular degeneration, and diabetic retinopathy) and/or objective VA measurements, here we used multiple metrics of vision loss, objective distance and near VA and subjective visual function, as our primary variables of interest and include several methods for evaluating cognitive function.

When assessed independently after controlling for a wide range of potential confounders, measured VI at distance and near was associated with 5.1-point and 3.8-point decreases, respectively, in DSST scores compared with participants with good visual acuity. Self-reported VI more closely resembled distance than near VI, with a 5.3-point decrease in DSST scores compared with participants reporting no VI. Considering that the middle 50% of the NHANES study group scored within a 25-point range on the DSST, even a 5-point decrease is noteworthy.

These relationships were significant in our logistic regression models of DSST impairment for distance VI and self-reported VI but not for near VI. We also found that self-reported VI was associated with 1.9-fold to 2.6-fold increased odds of dementia as classified by NHATS. This is the first evidence, to our knowledge, of a strong, clear association between self-reported VI and cognitive impairment in a large-scale, broadly representative sample of the US population.

Implications and Impact

There appears to be a substantial association between VI and worse cognitive performance, even after accounting for other age-related predictors of cognitive decline including hearing and physical function impairments. This is timely and relevant to an aging society, highlighting the importance of identifying VI in this population. Our results support last year’s recommendations by the Health and Medicine Division of the National Academies of Sciences, Engineering, and Medicine (formerly Institute of Medicine) to make eye health a population health imperative, with vision screenings, epidemiology and population-based research, and public health infrastructure to improve eye health awareness and access to care.38

Screening for blindness and VI has been a well-debated topic in the United States. In 2009 and again in 2016, the US Preventive Services Task Force concluded there was insufficient evidence to recommend vision screening given lack of improvement in VA or clinical outcomes over time.33,39,40 This is further evidenced by a review of the Cochrane library that suggests community screening of asymptomatic older adults does not improve vision.41 The US Preventive Services Task Force followed rigorous methods; however, evaluation of vision screening is a complex and nuanced matter. There remains controversy surrounding the recommendation because some perceive the US Preventive Services Task Force to have had too narrow a focus. The American Academy of Ophthalmology and others support the need for vision screening in the older population, claiming strong and compelling reasons for screening owing to the quality of life impact of vision and the availability of treatments for many of the most common etiologies of poor vision including uncorrected refractive error, cataract, and age-related macular degeneration.42,43 Additionally, Healthy People 2020 is a federal program designed to improve the health of Americans and includes vision screening as part of their objectives.44 Finally, a Centers for Disease Control and Prevention expert panel on vision surveillance provided recommendations for developing an effective vision screening system, one that incorporates self-reported visual function along with standard tests of VA.45

Limitations

Despite this study’s strengths, we recognized that cognition is a multidimensional construct that no single test can comprehensively measure; therefore, we used 2 data sets with varying cognitive tests of memory, orientation, and executive functioning. Quiz Ref IDHowever, the potential for bidirectional confounding remains, with VI limiting the ability to obtain accurate cognitive testing and/or cognitive impairment complicating VA assessments owing to difficulty processing and communicating visual input. Although we were unable to completely mitigate this, the NHANES did provide safeguards: having participants wear reading glasses when needed, excluding blind participants, and excluding participants unable to complete a practice exercise owing to visual, physical, or cognitive impairments, as determined by a trained interviewer.46 Furthermore, the NHATS data substantiated results from the NHANES while using different criteria for dementia classification that involved mostly nonvisual cognitive function tasks. This consistency supports a real association between VI and poor cognitive function.

Importantly, the results presented in this cross-sectional analysis are purely observational. A causative relationship between VI and cognitive dysfunction cannot be established without longitudinal studies. We also cannot exclude the effects of nonresponse bias for those who did not complete the DSST or dementia evaluation or recall bias for data collected by self-report. Furthermore, just as cognitive impairment may complicate the evaluation of vision, it can also call into question the reliability of using self-reported measures.

Conclusions

In summary, VI is significantly associated with worse cognitive function after adjusting for demographics, health, and other factors in this cross-sectional analysis of 2 nationally representative samples of the US population. These findings were most pronounced for VA measured at distance and by self-report and highlight the importance of accounting for cognitive impairment as an outcome in future studies aimed at reducing VI in older adults, including randomized clinical trials of vision screening. Further research is warranted to better understand longitudinal and causal relationships between visual and cognitive decline. However, from a policy perspective, should causality be established, this may contribute to the value of vision screening, not only to identify patients who may benefit from treatment of correctable eye diseases but also to suspect broader limitations in function from cognitive and directly visual tasks.

Back to top
Article Information

Corresponding Author: Suzann Pershing, MD, MS, Byers Eye Institute, Department of Ophthalmology, Stanford University School of Medicine, 2452 Watson Ct, Palo Alto, CA 94303 (pershing@stanford.edu).

Accepted for Publication: June 22, 2017.

Published Online: August 17, 2017. doi:10.1001/jamaophthalmol.2017.2838

Author Contributions: Dr Pershing and Ms Chen had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Chen.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Chen, Bhattacharya.

Obtained funding: Chen.

Supervision: Bhattacharya, Pershing.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Pershing is a consultant with equity interest in Digisight Technologies, San Francisco, California. No other disclosures are reported.

Funding/Support: Funding was received from the Stanford University School of Medicine MedScholars Fund (Ms Chen); grants R37 AG036791 and P30 AG7253 from the National Institute on Aging (Dr Battacharya); and from the Research to Prevent Blindness, Inc (Dr Pershing).

Role of the Funder/Sponsor: The funding organizations did not have a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review or approval of the manuscript; or decision to submit the manuscript for publication.

References
1.
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States.  Arch Ophthalmol. 2004;122(4):477-485.PubMedGoogle ScholarCrossref
2.
Evans  JR, Fletcher  AE, Wormald  RP,  et al.  Prevalence of visual impairment in people aged 75 years and older in Britain: results from the MRC trial of assessment and management of older people in the community.  Br J Ophthalmol. 2002;86(7):795-800.PubMedGoogle ScholarCrossref
3.
Tielsch  JM, Sommer  A, Witt  K, Katz  J, Royall  RM.  Blindness and visual impairment in an American urban population: the Baltimore Eye Survey.  Arch Ophthalmol. 1990;108(2):286-290.PubMedGoogle ScholarCrossref
4.
Graham  JE, Rockwood  K, Beattie  BL,  et al.  Prevalence and severity of cognitive impairment with and without dementia in an elderly population.  Lancet. 1997;349(9068):1793-1796.PubMedGoogle ScholarCrossref
5.
Hedden  T, Gabrieli  JDE.  Insights into the ageing mind: a view from cognitive neuroscience.  Nat Rev Neurosci. 2004;5(2):87-96.PubMedGoogle ScholarCrossref
6.
Brookmeyer  R, Johnson  E, Ziegler-Graham  K, Arrighi  HM.  Forecasting the global burden of Alzheimer’s disease.  Alzheimers Dement. 2007;3(3):186-191.PubMedGoogle ScholarCrossref
7.
Prince  M, Wimo  A, Guerchet  M,  et al. World Alzheimer Report 2015: the Global Impact of Dementia analysis of prevalence, incidence, cost, and trends. http://www.alz.co.uk.laneproxy.stanford.edu/research/WorldAlzheimerReport2015.pdf. Accessed August 19, 2016.
8.
Varma  R, Vajaranant  TS, Burkemper  B,  et al.  Visual impairment and blindness in adults in the united states: demographic and geographic variations from 2015 to 2050.  JAMA Ophthalmol. 2016;134(7):802-809.PubMedGoogle ScholarCrossref
9.
Ong  SY, Cheung  CY, Li  X,  et al.  Visual impairment, age-related eye diseases, and cognitive function: the Singapore Malay Eye study.  Arch Ophthalmol. 2012;130(7):895-900.PubMedGoogle ScholarCrossref
10.
Clemons  TE, Rankin  MW, McBee  WL; Age-Related Eye Disease Study Research Group.  Cognitive impairment in the Age-Related Eye Disease Study: AREDS report no. 16.  Arch Ophthalmol. 2006;124(4):537-543.PubMedGoogle ScholarCrossref
11.
Baker  ML, Wang  JJ, Rogers  S,  et al.  Early age-related macular degeneration, cognitive function, and dementia: the Cardiovascular Health Study.  Arch Ophthalmol. 2009;127(5):667-673.PubMedGoogle ScholarCrossref
12.
Bowen  M, Edgar  DF, Hancock  B,  et al. The Prevalence of Visual Impairment in People with Dementia (the PrOVIDe study): a cross-sectional study of people aged 60-89 years with dementia and qualitative exploration of individual, carer and professional perspectives. In:  Health Services and Delivery Research. Southampton, England: NIHR Journals Library; 2016.
13.
Pham  TQ, Kifley  A, Mitchell  P, Wang  JJ.  Relation of age-related macular degeneration and cognitive impairment in an older population.  Gerontology. 2006;52(6):353-358.PubMedGoogle ScholarCrossref
14.
Woo  SJ, Park  KH, Ahn  J,  et al.  Cognitive impairment in age-related macular degeneration and geographic atrophy.  Ophthalmology. 2012;119(10):2094-2101.PubMedGoogle ScholarCrossref
15.
Rait  G, Fletcher  A, Smeeth  L,  et al.  Prevalence of cognitive impairment: results from the MRC trial of assessment and management of older people in the community.  Age Ageing. 2005;34(3):242-248.PubMedGoogle ScholarCrossref
16.
Garin  N, Olaya  B, Lara  E,  et al.  Visual impairment and multimorbidity in a representative sample of the Spanish population.  BMC Public Health. 2014;14:815-825.PubMedGoogle ScholarCrossref
17.
Court  H, McLean  G, Guthrie  B, Mercer  SW, Smith  DJ.  Visual impairment is associated with physical and mental comorbidities in older adults: a cross-sectional study.  BMC Med. 2014;12:181-188.PubMedGoogle ScholarCrossref
18.
Mangione  CM, Seddon  JM, Cook  EF,  et al.  Correlates of cognitive function scores in elderly outpatients.  J Am Geriatr Soc. 1993;41(5):491-497.PubMedGoogle ScholarCrossref
19.
Salthouse  TA, Hancock  HE, Meinz  EJ, Hambrick  DZ.  Interrelations of age, visual acuity, and cognitive functioning.  J Gerontol B Psychol Sci Soc Sci. 1996;51(6):317-330.PubMedGoogle ScholarCrossref
20.
Lin  FR, Metter  EJ, O’Brien  RJ, Resnick  SM, Zonderman  AB, Ferrucci  L.  Hearing loss and incident dementia.  Arch Neurol. 2011;68(2):214-220.PubMedGoogle ScholarCrossref
21.
Lin  FR.  Hearing loss and cognition among older adults in the United States.  J Gerontol A Biol Sci Med Sci. 2011;66(10):1131-1136.PubMedGoogle ScholarCrossref
22.
Lin  FR, Yaffe  K, Xia  J,  et al; Health ABC Study Group.  Hearing loss and cognitive decline in older adults.  JAMA Intern Med. 2013;173(4):293-299.PubMedGoogle ScholarCrossref
23.
Gurgel  RK, Ward  PD, Schwartz  S, Norton  MC, Foster  NL, Tschanz  JT.  Relationship of hearing loss and dementia: a prospective, population-based study.  Otol Neurotol. 2014;35(5):775-781.PubMedGoogle ScholarCrossref
24.
Dupuis  K, Pichora-Fuller  MK, Chasteen  AL, Marchuk  V, Singh  G, Smith  SL.  Effects of hearing and vision impairments on the Montreal Cognitive Assessment.  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2015;22(4):413-437.PubMedGoogle ScholarCrossref
25.
Lin  MY, Gutierrez  PR, Stone  KL,  et al; Study of Osteoporotic Fractures Research Group.  Vision impairment and combined vision and hearing impairment predict cognitive and functional decline in older women.  J Am Geriatr Soc. 2004;52(12):1996-2002.PubMedGoogle ScholarCrossref
26.
Yamada  Y, Denkinger  MD, Onder  G,  et al.  Dual sensory impairment and cognitive decline: the results from the Shelter Study.  J Gerontol A Biol Sci Med Sci. 2016;71(1):117-123.PubMedGoogle ScholarCrossref
27.
Won  H, Singh  DK, Din  NC,  et al.  Relationship between physical performance and cognitive performance measures among community-dwelling older adults.  Clin Epidemiol. 2014;6:343-350.PubMedGoogle Scholar
28.
Centers for Disease Control and Prevention; National Center for Health Statistics. National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes.htm/. Published 2016. Accessed December 19, 2016.
29.
Proust-Lima  C, Amieva  H, Dartigues  J-F, Jacqmin-Gadda  H.  Sensitivity of four psychometric tests to measure cognitive changes in brain aging-population-based studies.  Am J Epidemiol. 2007;165(3):344-350.PubMedGoogle ScholarCrossref
30.
National Institute on Aging Health ABC Operations Manual. Digit symbol substitution test. https://healthabc.nia.nih.gov/sites/default/files/dsst_0.pdf. Accessed March 7, 2017.
31.
Rosano  C, Newman  AB, Katz  R, Hirsch  CH, Kuller  LH.  Association between lower digit symbol substitution test score and slower gait and greater risk of mortality and of developing incident disability in well-functioning older adults.  J Am Geriatr Soc. 2008;56(9):1618-1625.PubMedGoogle ScholarCrossref
32.
Swindell  WR, Cummings  SR, Sanders  JL,  et al.  Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.  Rejuvenation Res. 2012;15(4):405-413.PubMedGoogle ScholarCrossref
33.
Chou  R, Dana  T, Bougatsos  C, Grusing  S, Blazina  I.  Screening for impaired visual acuity in older adults: Updated evidence report and systematic review for the us preventive services task force.  JAMA. 2016;315(9):915-933.PubMedGoogle ScholarCrossref
34.
National Health and Aging Trends Study (NHATS) User Guide. https://healthabc.nia.nih.gov/sites/default/files/dsst_0.pdf. Accessed February 2, 2017.
35.
STATA programming statements for construction of dementia classification in the National Health and Aging Trends Study. https://www.nhats.org/scripts/documents/NHATS_Addendum_to_Technical_Paper_5_STATA_Programming_Statements_Jul2013.pdf. Accessed February 5, 2017.
36.
Classification of Persons by Dementia Status in the National Health and Aging Trends Study. https://www.nhats.org/scripts/documents/DementiaTechnicalPaperJuly_2_4_2013_10_23_15.pdf. Accessed February 2, 2017.
37.
Addendum to classification of persons by dementia status in the National Health and Aging Trends Study for rounds 2-5. https://www.nhats.org/scripts/documents/NHATS_Dementia_Classification_Addendum_Rounds_2_5.pdf. Accessed May 30, 2017.
38.
Teutsch S, McCoy M, Woodbury B, Welp A, et al. Making eye health a population health imperative: vision for tomorrow: a report of the national academies of sciences, engineering, and medicine health and medicine division. http://www.nationalacademies.org/hmd/Reports/2016/making-eye-health-a-population-health-imperative-vision-for-tomorrow.aspx. Published 2016. Accessed October 20, 2016.
39.
US Preventive Services Task Force.  Screening for impaired visual acuity in older adults: US Preventive Services Task Force recommendation statement.  Ann Intern Med. 2009;151(1):37-43, W10.PubMedGoogle ScholarCrossref
40.
Lee  P.  Visual acuity screening among asymptomatic older adults.  JAMA. 2016;315(9):875-876.PubMedGoogle ScholarCrossref
41.
Smeeth  L, Iliffe  S.  Community screening for visual impairment in the elderly.  Cochrane Database Syst Rev. 2006;(3):CD001054. PubMedGoogle Scholar
42.
Sommer  A.  The USPSTF position on vision screening of adults—seeing is believing?  JAMA Intern Med. 2016;176(4):438-439.PubMedGoogle ScholarCrossref
43.
Parke  DW  II, Repka  MX, Lum  F.  The US Preventive Services Task Force recommendation on vision screening in older adults: a narrow view.  JAMA Ophthalmol. 2016;134:485-486.PubMedGoogle ScholarCrossref
44.
US Department of Health and Human Services; Office of Disease Prevention and Health Promotion. Healthy People 2020 Topics and Objectives: vision. https://www.healthypeople.gov/2020/topics-objectives/topic/vision. Accessed September 19, 2016.
45.
West  SK, Lee  P.  Vision surveillance in the United States: has the time come?  Am J Ophthalmol. 2012;154:S1-S2.Google ScholarCrossref
46.
National Health and Nutrition Examination Survey 1999-2000 Data Documentation, Codebook, and Frequencies: Cognitive Functioning (CFQ): Appendix 1: NHANES Digit Symbol Substitution Exercise (CFQ): Interviewer Instructions. https://wwwn.cdc.gov/Nchs/Nhanes/1999-2000/CFQ.htm#Appendix_1:__NHANES_DIGIT_SYMBOL_SUBSTITUTION_EXERCISE_(CFQ):_Interviewer_Instructions. Accessed May 30, 2017.
×